Understanding Poverty in Aceh During the Tsunami and Early Reconstruction Period

1. Understanding Poverty in AcehDuring the Tsunami and Early Reconstruction Period Jed Friedman, Ellen Tan, Enrique Blanco Armas, Sukma Yuningsih, The World Bank

2. Overview • These are the preliminary results of the poverty assessment for Aceh – comments welcome! • Aim: to deepen understanding of the poverty impacts of tsunami and reconstruction in Aceh • Overall, poverty in Aceh has increased slightly for both urban and rural areas from 2004 to 2005 • Relatively larger increases in tsunami-affected and post-conflict areas than in less affected areas

3. Context • The tragic 2004 Sumatran-Andaman earthquake and tsunami caused damage and loss, in both economic and human terms, of large proportions. • The global community, led by the Indonesian government, mobilized a reconstruction effort of unprecedented scale for a developing country. • Shortly after the tsunami, the Government of Indonesia and GAM reached an historic peace agreement. • The World Bank aims to assist the Government of Aceh in the formulation of a sustainable economic development strategy. This poverty assessment is the first study among several.

4. Approach • Individual and household welfare is multi-dimensional – e.g. income, wealth, health, “happiness” • Traditional economic analysis focuses on consumption as a summary measure of household resources • The focus here will be on consumption, but alternative dimensions – assets, health – will also be considered

5. Methods • Two principal data sources are employed: SUSENAS, a large scale socio-economic survey fielded annually by BPS – 10,200 in 2004 and 10,900 households in 2005. STAR, special purpose longitudinal survey that re-contacts a selection of 2004 SUSENAS households with an extensive questionnaire in 2005 – 5,300 households in total.

6. Methods (cont.) • SUSENAS records several key dimensions of socio-economic welfare: household composition, characteristics, and consumption as well as access to health and education services. • STAR records the identical information and supplements with it with a household record of tsunami and early reconstruction experiences. • SUSENAS is representative of the entire province, STAR only samples from tsunami affected districts – not everywhere in Aceh.

7. Methods (cont.) • We start with poverty lines in 2004 that yield the BPS 2004 estimates of poverty. • For 2005, in order to provide a welfare consistent update to the poverty line we: • 1. determine a consumption bundle representative to the poor in urban and rural areas, • 2. apply these consumption weights to the monthly BPS urban price series. • Limitations of this approach: price changes are measured only in Banda Aceh and Lhokseumawe. To what extent are these changes accurate to the rest of the province?

8. Summary results

9. Summary results Note: *Only includes Kabupaten not Kota

10. 2004 Aceh Poverty by District

11. 2004-2005 change in poverty, by district

12. 2005 Aceh Poverty by District

13. Summary results (cont.) • A slight increase in poverty while the national and neighboring (Sumut) trends were declining. • Larger increases in tsunami- and post-conflict (rural) areas areas suggest particular vulnerability to changes (disaster; price increases) in those areas. • Are these findings robust to different reference levels of consumption welfare (i.e. different poverty lines)?

14. Cumulative Distribution Function for Aceh

15. Rural Aceh

16. Urban Aceh

17. Robustness of findings to choice of poverty line • Analysis of CDFs suggest that measured poverty level is particularly sensitive to choice of poverty line. • Poverty lines within a broad range would still find a small increase or no change in poverty, especially in rural areas. • Households that were relatively well-off in 2004 did even better, on average, in 2005, especially for urban areas.

18. Who were the poor in 2004?

19. Who were the poor in 2004?- Relative Odds

20. Direct experience of tsunami for poor and non-poor • Direct tsunami experience was more common for the non-poor due to location at time of disaster. Among most heavily affected areas, little difference between poor and non-poor: OverallMost heavily damaged areas Poor Non-Poor Poor Non-Poor Mortality 6.5% 10.7% 19.3% 24.4% Heard the water 28.5% 34.5% 62.8% 63.7% Saw tsunami come ashore 19.2% 23.6% 47.5% 46.6% See people search for loved ones 24.7% 28.5% 51.2% 54.9%

21. Direct experience of tsunami for poor and non-poor – immediate aftermath • At time of STAR interview, roughly equal numbers of poor and non-poor with similar aftermath experiences: OverallMost heavily damaged areas Poor Non-Poor Poor Non-Poor Living in temporary housing 7.4% 8.4% 18.2% 18.3% Reliant on aid-provided water 5.9% 8.4% 21.8% 21.4% Receipt of tsunami related aid from government 43.7% 44.0% 68.0% 65.3% Receipt of tsunami related aid from NGOs 42.3% 40.5% 70.3% 67.6%

22. Direct impacts of tsunami on poor and non-poor – asset loss Percentage of households experiencing property damage (conditional on ownership) in heavily damaged areas: PoorNon-Poor Housing: 60% 62% Land: 26% 28% Crops: 51% 64% Livestock: 48% 65% Household goods: 64% 61% Transport: 50% 56% Gold/Jewelry: 46% 53% Damage rates range from: 15-30% in moderately affected areas 1-5% in unaffected areas for both poor and non-poor

23. Direct impacts of tsunami – mental health • We already looked at assets – tsunami impacts substantial regardless of poverty status • Now look at one dimension of health: post-traumatic stress - “Post Traumatic Stress Reaction Index” measured in STAR and varies from 0-21 • Much higher level in damaged areas, but little difference between poor and non-poor within those areas - Only 8% of individuals with high scores had received counseling

24. Who were the poor in 2005?

25. Who were the poor in 2005?- Relative Odds

26. Relative Odds in 2004 and 2005 (cont.)

27. Relative Odds in 2004 and 2005 (cont.) Note: Only includes Kabupaten not Kota

28. Predictors of poverty transitions over 2004-5 • The poor is not a static group – some people exited poverty over 2004-5 and slightly more people entered • What are the factors significantly associated with the transition out of poverty? • Small household sizes: an increase in one household member reduces the odds of escape by 32% • Education: an increase in one year of schooling for the household head increases the odds of escape by 10% • Productive assets: having a non-farm business increases the likelihood of escape by 100% • Disaster assistance: the receipt of government aid increases the likelihood of escape by 42%

29. Predictors of poverty transitions over 2004-5 (cont.) • What are the factors significantly associated with protection from the transition into poverty? • Small households: an increase in one household member raises the odds of entry by 38% • Productive assets: having a non-farm business reduces the likelihood of entry by 50%, and one year of education by 10% • Crop diversification: Agricultural households that only grow rice are more vulnerable to entering poverty (30% more likely) while those that grow perennials and other crops are 32% less likely to enter poverty • Disaster assistance: the receipt of NGO aid reduces the likelihood of entering poverty by 23%

30. Concluding remarks • The slight rise in poverty masks a good deal of underlying heterogeneity • Most poor are rural and work in agriculture - the overall size of this group may have increased over the period • Both poor and non-poor in tsunami areas were seriously affected in a variety of dimensions • However the growth in urban areas under reconstruction has led to relatively faster income growth for the better-off (and most likely better educated)

31. Concluding remarks (cont.) • Tsunami aid appears to help poverty transitions but there are questions over targeting • Crop diversification and non-farm enterprises seem to be important for beneficial poverty transitions • Two vulnerable groups: the structurally poor (poor before tsunami) and the “shocked”, who suffered loss of private goods and assets however many retained key endowments. • Given limited public funds for poverty alleviation, what is the most efficient group to target?

32. Next steps • Investigate possible other sources of local price information and discuss inclusion into the analysis • Investigate other dimensions of welfare, most importantly access to public services such as health and education